Title: A Study of Foreclosures From 2005-2014 Using Statistical Monitoring and Disease Mapping Approaches

Abstract: In the United States, one component of the Great Recession was the bust of the subprime housing bubble, leading to a drop in housing prices by an average of 26% from June 2006 to November 2010, a decline not seen since the Great Depression. The near perfect storm of financial engineering, credit expansion, and the evaporation of underwriting and credit standards led to a wave of mortgage default and foreclosure on a massive scale. The enormous social and economic consequences of these events motivate the study of foreclosure. This talk describes two statistical methods used to study foreclosure. First, a statistical process monitoring approach based on cumulative sum charts is developed that monitors foreclosure rates in the housing market. This methodology is unique among similar charts due to its spatial risk adjustment and ability to consider simultaneous events with differing baseline risk. The method is illustrated using 370,517 mortgage records in Wayne County, Michigan between 2005 and 2014. Second, a disease mapping approach is adapted from epidemiology to model the spatial risk of foreclosure more formally. A fully Bayesian hierarchical model for areal data that includes fixed effects, random county-level effects, and conditional autoregressive effects to account for spatial variation is considered.